Low-Light Video System

ABSTRACT

Real time, low-light images, for example, obtained from the fluorescent marker for identifying tumors during surgery, are combined to improve the signal-to-noise ratio using a motion signal derived from corresponding high-light images, for example, taken with a second camera at interleaved intervals of higher illumination.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

This invention was made with government support under 1846884 awarded bythe National Science Foundation. The government has certain rights inthe invention.

BACKGROUND OF THE INVENTION

The present invention relates to a medical imaging system for detectingfaint fluorescence signals and in particular to a fluorescence imagingsystem usable in brightly lit environments, for example, a surgicalsuite.

Fluorescent marker compounds that target cancerous tumors hold promisein allowing rapid identification of ex vivo tissue, for example, asobtained from a biopsy. The fluorescence signal developed by such markercompounds is relatively faint and normally viewed with specialfluorescent microscopes that selectively illuminate the tissue with aproper exciting waveform and that employ sensitive imaging systems thatcan isolate and detect the returned fluorescence signal. Multiphoton andconfocal microscope optics, for example, may be used to isolate thefluorescence signal from specific tissue while image intensifiers, suchas photomultiplier tubes or the like, may be used to amplify the faintsignal for detection.

While such fluorescent markers potentially simplify the identificationof tumors, the ability of fluorescent markers to guide a surgicalprocedure is limited by the time required to transport tissue samples toa remote location suitable for fluorescence analysis. Alternatively, thesamples are imaged in the operating room, often before extraction fromthe patient. In this scenario, ambient illumination remains active butis dimmed, and light filters are typically used and this limits thespeed, sensitivity, and applicability of the method due to the reducedsignal and added background noise. Alternatively the ambient light needsto be switched off periodically during surgery, interrupting theworkflow of the entire team.

U.S. Pat. 10,045,696 entitled “Tissue Fluorescence Monitor with AmbientLight Rejection” assigned to the assignees of the present invention andhereby incorporated by reference, describes a fluorescence imagingsystem that operates in coordination with a rapidly switched ambientlighting system, the latter turning the ambient lighting on and off at aspeed imperceptible to the human eye. The short periods of darknessduring the switching process are exploited to perform fluorescenceimaging without significant interference from the ambient light. Bymaking fluorescence imaging compatible with bright illumination, theinvention allows the fluorescence imaging equipment to be moved into asurgical suite or used in modified form for in vivo examination oftissue.

In many important applications of fluorescence imaging, the fluorescentimages remain faint, having only a few tens of photons per pixel perframe. This can be remedied by aligning and then combining successiveframes together, the alignment serving to reduce motion blur whileincreasing the quality of the image, for example, sharpness,contrast-to-noise ratio, or signal-to-noise ratio. With extremelylow-light images, however, accurate alignment is difficult and thereforeincreased blur occurs.

SUMMARY OF THE INVENTION

The present inventors have recognized that a “high-light” image, forexample, available in the switched ambient lighting system describedabove, co-registered with the low-light image produced by fluorescencemonitoring, can then be used as a proxy for determining the motion ofthe low-light image during the combination of successive low-lightimages. The result is a higher signal-to-noise ratio with improvedalignment and thus reduced motion blur. Combining the high-light andlow-light images with a properly trained neural network can providefurther reductions in artifacts caused from the low-light acquisitionand combination process.

Specifically, in one embodiment, the invention provides a low-lightvideo system having a having at least one camera that can receivelow-light from an imaged object to provide a sequence of low-light imageframes and high-light from the imaged object having a greater flux thanthe low-light to provide a sequence of high-light image frames. Anelectronic processor implements: (a) a motion extractor receiving thehigh-light image frames from the at least one camera to determine motionof the imaged object between high-light image frames; and (b) anintegrator combining low-light image frames after alignment according tothe motion determined by the motion extractor to output reduced noiselow-light image frames.

It is thus a feature of at least one embodiment of the invention toreduce the inadvertent introduction of errors into low-light images whenthey are combined to reduce noise resulting from errors in deducingmotion for low-light images.

In one embodiment, the invention may further include a neural networkreceiving the reduced noise low-light image frames and outputtingcorrected low-light image frames, the neural network trained with ateaching set of pairs of low-light image frames with respectively higherand lower levels of noise with respect to a common imaged object.

It is thus a feature of at least one embodiment of the invention reduceartifacts in the motion correction process by using a neural net trainedto “ground truth” low-noise images.

The teaching set of low-light image frames may be images of tissue.

It is thus a feature of at least one embodiment of the invention toprovide a system well adapted for use in real-time surgicalapplications.

In one embodiment, each teaching set of pairs of low-light image framesmay include a fluorescence image of tissue and the same fluorescenceimage of tissue with added simulated noise.

It is thus a feature of at least one embodiment of the invention toprovide a simple method of determining a “ground truth” with respect toa fluorescent image. High signal-to-noise ratio fluorescent images maybe used for the ground truth and then degraded by the introduction ofnoise to complete the training set.

The teaching set of low-light image frames may represent images takenwith the at least one camera of the tissue, and the teaching set mayfurther include high-light image frames representing images taken withthe at least one camera of the tissue.

It is thus a feature of at least one embodiment of the invention toexploit the higher information content of the high-light signal used todeduce motion to also reduce artifacts in the motion correction processand otherwise inform the image reconstruction with respect to a class ofimaged objects such as tissue.

The low-light video system may further include an error detectorproducing an error signal indicating errors in the determined motionrelating to at least a portion of a high-light image frame, and theintegrator may use the error signal to exclude a portion of acorresponding low-light image frame from the combining.

It is thus a feature of at least one embodiment of the invention tolimit artifacts generated by abrupt changes between images, for example,a portion of an image being momentarily occluded by a surgicalinstrument, which might otherwise be erroneously interpreted as motion.

The error signal maybe produced by warping an early received high-lightimage frame according to the determined motion with respect to a laterreceived-light image frame and comparing the warped early receivedhigh-light image frame to the later received high-light image frame toidentify pixels having differences in value of more than a predefinedthreshold, the determine pixels providing the error signal.

It is thus a feature of at least one embodiment of the invention toprovide a simple mechanism for identifying motion detection errors.

The integrator may combine different numbers of low-light image framesfor different pixels of the low-light image frames. In one example, thenumber of low-light image frames may be determined according to a numberof low-light image frames occurring after an error signal including thegiven pixel.

It is thus a feature of at least one embodiment of the invention toprovide a simple method of eliminating frames with motion errors withoutintroducing additional artifacts by changing the window over whichpixels of different frames are combined.

The low-light video system may further include a synchronization circuitsynchronizing the acquisition of the sequence of low-light image framesand the sequence of high-light image frames with an area illuminatorswitching between an on-state and off-state so that the low-light imageframes are obtained only during the on-state and high-light image framesare obtained only during the off-state.

It is thus a feature of at least one embodiment of the invention to makeuse of surgical systems that provide momentary bright and darkenedambient illumination to obtain the necessary high-light and low-lightimage frames.

These particular objects and advantages may apply to only someembodiments falling within the claims and thus do not define the scopeof the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a simplified perspective view of a surgical suite suitable foruse with the present invention showing area illuminators, displaylights, and a surgical and desktop fluorescence imaging systemcoordinated by a control system;

FIG. 2 is a functional block diagram of the control system of FIG. 1receiving a sequence of low-light images and a high-light images fromco-registered cameras, and using the high-light images to deduce motion(optical flow) by means of a motion extractor which is then used tocontrol the combination of successive low-light images by an integratorfor improved signal-to-noise ratio and further showing a trained neuralnetwork receiving the integrated images to produce a reduced artifactoutput image;

FIG. 3 is a detailed block diagram of the integrator of FIG. 2 combiningsuccessive low-light images as guided by the extracted optical flow andan optical flow failure map; and

FIG. 4 is a block diagram of a training system for the neural network ofFIG. 2 .

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

Referring now to FIG. 1 , a surgical suite 10 or the like may providefor multiple area illuminators 12 a and 12 b, for example, positioned toilluminate an operating room table 15 holding a patient 16 for surgery.In addition, the surgical suite 10 may include multiple display lights14 and other sources of light including, for example, display lights 14providing for visual signals, for example, an illuminated sign displaylight 14′ (e.g., an exit sign) or a computer monitor display light 14″(e.g., an LCD backlight or LED array), presenting data to an attendingphysician.

The surgical suite 10 may further hold a desktop fluorescence microscope18 for use contemporaneously with surgery to analyze ex vitro tissuefrom the patient 16 or a surgical fluorescence surgical imaging system20, for example, suspended for direct viewing of tissue of the patientin vivo, or at the tip of an endoscope which may provide for microscopicor macroscopic imaging as will be described.

Each of these sources of ambient light (12 and 14) may intercommunicateas indicated by logical communication channel 22 with a controller 19 toswitch rapidly between an on-state 24 in which light is output and anoff-state 26 in which no light is output indicated schematically by anambient illumination signal 27. The logical communication channel 22will be discussed below and may take a variety of forms not limited to,for example, a wired network.

The ambient illumination signal 27 has a frequency, intensity, andon-state duration so that the output light flashes at a ratesubstantially above a flicker fusion rate at which the human eyeperceives a flashing. The flicker fusion rate is dependent onillumination brightness and other factors but in the present inventionwill typically be in excess of 24 Hz and preferably above 300 Hz.Generally the intensity of light during the on-state 24 will be suchthat an average intensity, that is, the intensity of the on-state 24times the duty cycle of the on-state 24, provides a desired perceivedlevel of illumination comparable to standard illumination levels. Dutycycle refers to the on-state 24 duration divided by the time betweensuccessive on-states 24.

Each of the sources of ambient light (12 and 14) may employ a lightsource that provides substantially white light and which may be rapidlyswitched between full and no illumination with minimal warm-up time orafterglow to have a rise and fall time constant that is preferably morethan five times faster than the frequency of the illumination signal 27.Standard light emitting diodes (LEDs) may be used for this purpose,which employ an ultraviolet LED emitter exciting a phosphor or similarmaterial if the phosphor has a short fluorescence lifetime on the orderof tens of microseconds. Alternatively, the light emitting diodes mayemploy a combination of red, green, and blue (and optionally orange)light emitting diodes and no phosphor to simulate white light with nophosphor afterglow.

Referring still to FIG. 1 , the surgical imaging system 20 may providefor an exciting light source 25, for example, a laser having a frequencyappropriate to excite fluorescence in fluorescent marker compounds 28 intissue of the patient 16. In one nonlimiting example, the exciting lightsource 25 may provide near infrared light suitable for stimulatingindocyanine dyes. The exciting light source 25 may also communicate asindicated by logical communication channel 22 with the controller 19 toswitch rapidly between an on-state 24 in which light is output and anoff-state 26 in which no light is output indicated schematically by anexciting illumination signal 29. Importantly, the on-state 24 of theexciting illumination signal 29 is coordinated to align with theoff-state 26 of the ambient illumination signal 27 so as to allowfluorescent imaging with reduced interference from the ambient lightingwhile reducing exhaustion of the fluorescent material.

Referring now to FIG. 2 , the surgical imaging system 20 may provide afirst low-light camera 30 and second high-light camera 32 co-registeredwith the low-light camera 30 to image tissue of the patient 16 along acommon imaging axis 34. This co-registration may be obtained, forexample, by means of a beam splitter 36 dividing the light from thetissue of the patient 16 between the low-light camera 30 and high-lightcamera 32, which may share a common lens system 38. Alternatively, thecameras may have roughly aligned but independent optical paths and theregistration may be done digitally by an electronic computer. In somecontemplated embodiments, a single camera can capture both the low-lightand high-light images with either a mechanically switched filter or abayer pattern filter array over the pixels.

The low-light camera 30 will be used to acquire fluorescence imagingdata and in that respect may have a blocking filter 39 providing afilter passing light in the desired wavelength range of the florescentsignal from the tissue of the patient 16. In one embodiment, the filtermay be adapted to pass near-infrared light, for example, from a fromfluorescent agent such as indocyanine green (ICG).

The low-light camera 30 is desirably a single photon type camera such asa single photon avalanche diode array (SPAD) or Quanta Image Sensor(QIS) providing a high time resolution (less than 100 ps) andsensitivity down to individual photons. The low-light camera 30 may havea low resolution, for example, less than 1000 pixels, or no more than 32× 32 pixels, although the inventors contemplate that higher resolutionsmay be useful as such systems become available, including 1024 × 500pixel arrays.

The high-light 32 camera 30 may be a standard CMOS camera providingcolor imaging and a spatial resolution of greater than the low-lightcamera 30, for example, having a resolution higher than the low-lightcamera 30, for example, in excess of 1 million pixels, for example,providing at least 1920 × 1080 pixels.

Each of cameras 30 and 32 will produce a respective set of low-lightframes 40 and high-light frames 42, for example, at a frame ratedictated by a fraction of the frequency of the signals 27 and 29 andtypically at a rate above the flicker fusion rate of about 40-60 framesper second.

The high-light frames 42 are provided to the controller 19 whichimplements a motion extractor determining motion of the tissue of thepatient 16 being imaged from successive frames to produce an opticalflow signal 46. This optical flow signal 46 provides a set of vectorsfor each pixel of the frames 42 indicating the relative motion directionand distance for that pixel with respect to the previous frame 42. In anonlimiting example, the motion extraction can be performed using theGunnar- Farnebäck optical flow algorithm described in Farnebäck G.(2003) “Two-Frame Motion Estimation Based on Polynomial Expansion,” in:Bigun J., Gustavsson T. (eds) Image Analysis, SCIA 2003, Lecture Notesin Computer Science, vol 2749, Springer, Berlin, Heidelberg.

The optical flow signal 46, the high-light frames 42, and the low-lightframes 40 are then provided to an integrator 50 which uses the opticalflow signal to align successive low-light frames 40 for an integrationprocess that sums the images on a pixel-by-pixel basis to improve thesignal-to-noise ratio as will be discussed below. The result is a set ofoptical flow denoised frames 52.

The denoised frames 52 and the high-light frames 42 are then provided toa trained neural network 54 to remove artifacts caused by the warping ofthe images by the integrator 50 used to correct for optical flow. Theneural network 54 per its training (which will be described in moredetail below) may also perform denoising of the images and may augmentthe information of the low-light frames 40 (via the denoised frames 52)with the information contained in the high-light frames 42.

The output of the neural network 54 provides reduced noise low-lateimage frames which may be output to display 14, for example, for useduring surgery or may be used in any subsequent process requiringinformation from fluorescent imaging or the like.

Referring now to FIG. 3 , the integrator 50 will receive successivehigh-light frames 42, for example, at times t-1 and t, and use theoptical flow signal 46 to warp the image from t-1 as indicated bywarping block 56 according to the optical flow signal 46 obtainedbetween times t-1 and t. This warped high-light frame of t-1 is thencompared to the high-light frame 42 at t to compute a pixel-by-pixeldifference between these frames at process block 58. These differencevalues are applied to a thresholder 59 comparing each difference valueto a predetermined threshold defining a point at which the pixeldifference likely indicates a motion detection error. The outputs of thethresholder 59 provide a binary mask value 60 for each pixel of a frame42 to create an optical flow failure map 62 for time t. Successiveoptical flow failure maps 62 are generated for each successive frame 42.

It will be appreciated that if the warping process of warping block 56perfectly corrects for motion between times t-1 and t of the high-lightframes 42 then the optical flow failure map 62 will have values of zerofor all pixels. On the other hand, differences between successive frames42 after warping of the earlier frame for motion, for example, becauseone image may be occluded by a surgical instrument or the like, willproduce values of one in the optical flow failure map 62 for the pixelsin that region of occlusion. More generally the optical flow failure map62 will reflect any significant difference between the warped andcurrent image not limited to occlusion.

The optical flow failure map 62 is used to reset a set of averagingcounters 64 that provide a running total of the number of successiveframes in which a given pixel has not been subject to an optical flowfailure. Use of the averaging counters 64 will be described later. Likethe optical flow failure map 62, the averaging counters 64 provide acount value for each pixel of a frame 42, and snapshots of the averagingcounters 64 may be stored for each frame time.

The optical flow signal 46 is also used to warp a current denoised frame70 which represents a running integration of motion-corrected low-lightframes 40 as will now be described. In this process, a current denoisedframe for time t-1 is received by warping block 72 also receiving theoptical flow signal 46 to warp the current denoised frame for time t-1to the current time t. This warped frame 74 is then multiplied by theoptical flow failure map 62 at multiplier 76 so that the warped frame 74only includes valid pixels (with invalid pixels zeroed). The resultingmasked signal 80 is then summed with the current low-light frame 40 atsumming block 82, and this used to provide the next denoised frame 70for time t.

Each denoised frame 70 as it is computed is then normalized by divider84 on a pixel-by-pixel basis by dividing the value of each pixel by theaveraging counters 64 for that pixel. This division process compensatesfor the fact that the pixel values will represent integrations overdifferent durations according to the last occurrence of an optical flowfailure.

The output of the divider 84 then provides the denoised frames 52 whichare input to the neural network shown in FIG. 2 . In one embodiment, theneural network 54 receives five consecutive denoised frames 52 togetherwith the corresponding values of the averaging counters 64 andhigh-light frames 42.

Referring now to FIG. 4 , the neural network 54 may in one embodimentprovide an architecture following the teachings of FastDVNet asdescribed in Matias Tassano, Julie Delon, and Thomas Veit: DVDNet: Afast network for deep video denoising, in 2019 IEEE InternationalConference on Image Processing (ICIP), pages 1805-1809, 2019.

Training of the neural network 54 is performed with a set of noisyfluorescent frames 100 in pairs with corresponding ground truthfluorescent frames 102. Both frames of each pair may be derived fromtissue samples injected with indocyanine green, for example, into thefemoral artery of a chicken thigh manipulated over many frames tosimulate vascular surgery. Imaging of this vascularized tissue andinjected dye provide high visual contrast, low-noise images that can beused as the ground truth fluorescent frames 102. The noisy fluorescentframes 100 are then prepared by reducing the signal strength andintroducing noise 104 of a type expected for the particular detector(random additive Poisson noise for a SPAD detector) and other types ofnoise such as spatial distortion expected from the warping process ofthe present invention, blurring from a combination of successive framesand quantization noise. The training set may also include ahigh-resolution image 104 obtained contemporaneously with a camerasimilar to high-light camera 32 and registered with the frame 102.Finally, the values of the averaging counters 64 for each pixel may beprovided.

The training process cycles through these training set values to trainthe weights of the neural network 54 and may use a mean square errorloss function in the training process and optimization using the ADAMOptimizer described in Diederik P. Kingma and Jimmy Ba: Adam: A methodfor stochastic optimization, in Yoshua Bengio and Yann LeCun, editors,3rd International Conference on Learning Representations, ICLR 2015, SanDiego, CA, USA, May 7-9, 2015, Conference Track Proceedings, 2015.

While the invention has been described in a medical context for imagingtissue, it will be appreciated that the same principles can be appliedto nonmedical applications including for example LiDAR systems, thermalimaging, polarimetry, hyperspectral imaging, images of materialscattering, non-line of sight imaging, and others, where there aredifferent received illumination signals with substantially differentflux, so that the stronger signal can allow motion tracking to permitintegration of the weaker signal to improve its signal-to-noise ratio.

Certain terminology is used herein for purposes of reference only, andthus is not intended to be limiting. For example, terms such as “upper”,“lower”, “above”, and “below” refer to directions in the drawings towhich reference is made. Terms such as “front”, “back”, “rear”, “bottom”and “side”, describe the orientation of portions of the component withina consistent but arbitrary frame of reference, which is made clear byreference to the text and the associated drawings describing thecomponent under discussion. Such terminology may include the wordsspecifically mentioned above, derivatives thereof, and words of similarimport. Similarly, the terms “first”, “second” and other such numericalterms referring to structures do not imply a sequence or order unlessclearly indicated by the context.

The term “frame” as used herein is intended to describe an array of atleast two dimensions of pixels taken at a given time interval andincludes frames where each pixel is a single intensity value or ahistogram of fluorescence lifetimes.

When introducing elements or features of the present disclosure and theexemplary embodiments, the articles “a”, “an”, “the” and “said” areintended to mean that there are one or more of such elements orfeatures. The terms “comprising”, “including” and “having” are intendedto be inclusive and mean that there may be additional elements orfeatures other than those specifically noted. It is further to beunderstood that the method steps, processes, and operations describedherein are not to be construed as necessarily requiring theirperformance in the particular order discussed or illustrated, unlessspecifically identified as an order of performance. It is also to beunderstood that additional or alternative steps may be employed.

References to “a controller”, “a processor”, or “a computer” can beunderstood to include one or more circuits that can communicate in astand-alone and/or a distributed environment(s), and can thus beconfigured to communicate via wired or wireless communications withother circuits. Generally, such a device may be dedicated circuitry suchas constructed from discrete components, an FPGA or ASIC or the like, ormay provide a standard computer architecture including one or moreprocessors such as a CPU, GPU, and/or one or more purpose-builtaccelerators and computer memory holding a data and a stored program.Such devices may be associated with or include standard input and outputdevices including a graphic display terminal, a keyboard, a voiceinterface, a touchscreen, a trackball, or mouse or the like and mayprovide for input/output connections through standard electronicinterfaces, level shifting circuits, and analog-to-digital anddigital-to-analog converters and/or digital interfaces employingstandard protocols for electrical communication. In particular, thepresent invention may provide for software and circuitry to interfacewith the above devices and other devices including for example othermedical systems according to protocols required for DICOM®, as well asto remote devices using the Internet, various wireless and wiredcommunications including IEEE 802.11, as well as various video and audiointerfaces of types well known in the art.

The memory may store one or more types of instructions and/or dataincluding those to implement the invention as described above, and topermit operation of the interfaces described above, and may includevolatile and/or non-volatile non-transitory computer readable media, forexample, RAM (Random Access Memory), flash memory, ROM (Read OnlyMemory), PROM (Programmable Read-Only Memory), EPROM (ErasableProgrammable Read-Only Memory), EEPROM (Electrically ErasableProgrammable Read-Only Memory), registers, disks, drives, or any othersuitable storage medium, or any combination thereof. The memory can be acomponent of a processor, can be operatively connected to a processorfor use thereby, or a combination of both.

It is specifically intended that the present invention not be limited tothe embodiments and illustrations contained herein and the claims shouldbe understood to include modified forms of those embodiments includingportions of the embodiments and combinations of elements of differentembodiments as come within the scope of the following claims. All of thepublications described herein, including patents and non-patentpublications are hereby incorporated herein by reference in theirentireties.

What we claim is:
 1. A low-light video system comprising: at least onecamera adapted to: receive low light from an imaged object to provide asequence of low-light image frames; receive high light from the imagedobject having a greater flux than the low light to provide a sequence ofhigh-light image frames; and an electronic processor implementing: (a) amotion extractor receiving the high-light image frames from the at leastone camera to determine motion of the imaged object between high-lightimage frames; and (b) an integrator combining low-light image framesafter alignment according to the motion determined by the motionextractor to output reduced noise low-light image frames.
 2. Thelow-light video system of claim 1 further including a neural networkreceiving the reduced noise low-light image frames and outputtingcorrected low-light image frames, the neural network trained with ateaching set of pairs of low-light image frames with respectively higherand lower levels of noise with respect to a common imaged object.
 3. Thelow-light video system of claim 2 wherein the higher and lower levels ofnoise are differences selected from the group consisting of randomadditive noise, spatial distortion, blurring, and quantization noise. 4.The low-light video system of claim 2 wherein the teaching set oflow-light image frames are of tissue.
 5. The low-light video system ofclaim 4 wherein each teaching set pair of low-light image frames includea fluorescence image of tissue and the same fluorescence image of tissuewith added simulated noise.
 6. The low-light video system of claim 4wherein the teaching set of low-light image frames represents imagestaken with the at least one camera of the tissue and wherein theteaching set further includes high-light image frames representingimages taken with the at least one camera of the tissue and where theneural network further receives the high-light image data.
 7. Thelow-light video system of claim 1 further including an error detectorproducing an error signal indicating errors in the determined motionrelating to at least a portion of a high-light image frame and whereinthe integrator uses the error signal to exclude a portion of acorresponding low-light image frame from the combining.
 8. The low-lightvideo system of claim 7 wherein the error signal is produced by warpingan early received high-light image frame according to the motion withrespect to a later received-light image frame and comparing the warpedearly received high-light image frame to the later received high-lightimage frame to identify pixels having differences in value of more thana predefined threshold, the determined pixels providing the errorsignal.
 9. The low-light video system of claim 1 wherein the integratorcombines different numbers of low-light image frames for differentpixels of the low-light image frames.
 10. The low-light video system ofclaim 1 further including an error detector producing an error signalindicating errors in the determined motion and wherein the integratorcombines different numbers of low-light image frames for different givenpixels of the low-light image frames according to a number of low-lightimage frames occurring after an error signal including the given pixel.11. The low-light video system of claim 1 further including asynchronization circuit synchronizing an acquisition of the sequence oflow-light image frames and sequence of high-light image frames with anarea illuminator switching between an on-state and off-state so that thelow-light image frames are obtained only during the on-state andhigh-light image frames are obtained only during the off-state.
 12. Thelow-light video system of claim 1 wherein the at least one cameraincludes a filter selectively passing infrared light and blockingvisible light.
 13. The low-light video system of claim 1 wherein thelow-light image frame have a lower image resolution than the high-lightimage frames.
 14. The low-light video system of claim 1 wherein the atleast one camera is a single photon camera.
 15. A method of low-lightimaging using a system including: at least one camera adapted to:receive low light from an imaged object to provide a sequence oflow-light image frames; receive high light from the imaged object havinga greater flux than the low light to provide a sequence of high-lightimage frames; and an electronic processor implementing: a motionextractor receiving the high-light image frames from the at least onecamera to determine motion of the imaged object between high-light imageframes; and an integrator combining low-light image frames afteralignment according to the motion determined by the motion extractor tooutput an image based on combined low-light image frames, the methodcomprising: (a) obtaining a sequence of low-light image frames and acorresponding sequence of high-light image frames of an object subjectto motion; (b) using the high-light image frames to deduce motion of thesubject; and (c) combining the low-light image frames after alignmentaccording to the motion deduced from the high-light image frames.